code: def test_quantize_openvino_with_tensor(self):
      model = mobilenet_v3_small(num_classes=10)
  
      x = torch.rand((1, 3, 256, 256))
      y = torch.ones((1,), dtype=torch.long)
  
      optimized_model = InferenceOptimizer.quantize(
          model, accelerator="openvino", calib_data=(x, y)
      )
  
      optimized_model(x[0:1])
  
imports: from unittest import TestCase
  from torchmetrics import F1Score
  from bigdl.nano.pytorch import Trainer
  from bigdl.nano.pytorch import InferenceOptimizer
  from torchvision.models.mobilenetv3 import mobilenet_v3_small
  from torchvision.models import resnet50
  import torch
  from torch import nn
  from torch.utils.data.dataset import TensorDataset
  from torch.utils.data.dataloader import DataLoader
  import tempfile
  import pytest
  import numpy
label_desc: Use image node_id 4 for calling the TestOpenVINO obj's underlying member method code with example usage: obj.test_quantize_openvino_with_tensor() without return types